I am using face-person-detection SSD model, trying to identify both people and faces in security scenarios, when the cameras are typically installed high above. I use the simple image as input, and this model was able to identify faces, but NOT standing people. There are indeed output returned with label == 1, which means this is a person; however, the probability is ~0.1. Why?
output from this model is:
The net outputs blob with shape: [1, 1, N, 7], where N is the number of detected bounding boxes. For each detection, the description has the format: [
image_id- ID of the image in the batch
label- predicted class ID
conf- confidence for the predicted class
y_min) - coordinates of the top left bounding box corner
y_max) - coordinates of the bottom right bounding box corner.
I was able to detect faces with label == 2. just not people. Thank you for helping out.
Did you resolve your issue by looking in the in-package documentation /opt/intel/computer_vision_sdk/deployment_tools/documentation/docs/face-person-detection-retail-0002.html?
Also, as you can see the pose coverage is standing upright, parallel to image plane so If the camera is to high the accuracy will be poor.
My image is taken at the horizontal position. I found the issue but I don't know how to solve it: the face-person-detection-retail-0002 has two output layers, including detection_out_face and detection_out_pedestrain. So in code, when I use outputInfo.begin()->first, it gives me the layer for face detection. I don't know how to enumerate to the pedestrian output later with outputInfo. I tried the end(), or , either worked.
Can you please let me know if a model contains several SSD, how can I get through all output layers?